NDLI: The Design of Neural Network Controller of a Class of Nonlinear Systems with Actuator Saturation

Content Provider	IEEE Xplore Digital Library
Author	Hui Fang Zhonghua Wang Bo Yang Min Fang
Copyright Year	2006
Description	Author affiliation: Sch. of Control Sci. & Eng., Jinan Univ. (Hui Fang; Zhonghua Wang; Bo Yang; Min Fang)
Abstract	The problem of actuator saturation appears in many practical control systems. If the controller is designed only with conventional linearly techniques, the presence of saturation can debase the performance even lead the closed-loop system to an unstable behavior. In this paper, neural net-based actuator saturation compensation scheme with on-line weights tuning law for the nonlinear systems in Brnovsky form is presented to decrease the influence of saturation. In this scheme, RBF neural network is adopted to approximate the part exceeding the saturation limit of controller's output. Another most prominent feature of the scheme is which can ensure the system is uniformly ultimately bounded which is proved by Lyapunov theory, and considering the network reconstruction error and the system's external disturbance. The tracking error can be freely adjusted by known form. The simulation example is given to illustrate the effectiveness of this method
Starting Page	949
Ending Page	952
File Size	182275
Page Count	4
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1712484
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Nonlinear control systems Control systems Nonlinear systems Sliding mode control Intelligent actuators Adaptive control Intelligent control Automation Electrical capacitance tomography sliding mode control actuator saturation neural network control adaptive control
Content Type	Text
Resource Type	Article

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